Sampling-Free Variational Inference of Bayesian Neural Nets.
Melih KandemirManuel HaußmannFred A. HamprechtPublished in: CoRR (2018)
Keyphrases
- neural nets
- variational inference
- posterior distribution
- bayesian inference
- markov chain monte carlo
- topic models
- feed forward
- probabilistic graphical models
- variational methods
- probabilistic model
- mixture model
- gaussian process
- back propagation
- neural network
- hyperparameters
- latent dirichlet allocation
- random sampling
- closed form
- probability distribution
- artificial neural networks
- exact inference
- latent variables
- approximate inference
- parameter estimation
- posterior probability
- graphical models
- learning tasks
- bayesian framework
- maximum a posteriori
- exponential family
- sample size
- bayesian networks
- prior information
- gaussian distribution
- regression model
- expectation maximization
- reinforcement learning
- probabilistic inference
- markov networks
- maximum likelihood
- text classification
- knowledge discovery
- information retrieval